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Predicting soil water content at -33 kPa by pedotransfer functions in stoniness 1 soils in northeast Venezuela
Pineda, M. C.; Viloria, J.; Martínez Casasnovas, José Antonio; Valera, A.; Lobo, D.; Timm, L. C.; Pires, L. F.; Gabriels, D.
Soil water content is a key property in the study of water available for plants, infiltration, drainage, hydraulic conductivity, irrigation, plant water stress and solute movement. However, its measurement consumes time and, in the case of stony soils, the presence of stones difficult to determinate the water content. An alternative is the use of pedotransfer functions (PTFs), as models to predict these properties from readily available data. The present work shows a comparison of different widely used PTFs to estimate water content at-33 kPa (WR - 33kPa ) in high stoniness soils. The work was carried out in the Caramacate River, an area of high interest because the frequent landslides worsen the quality of drinking water. The performance of all evaluated PTFs was compared with a PTF generated for the study area. Results showed that the Urach's PTF presented the best performance in relation to the others and could be used to estimate WR -33kPa in soils of Caramacate River basin. The calculated PTFs had a R2 of 0.65. This was slightly higher than the R2 of the Urach's PTF. The inclusion of the rock fragment volume could have the better results. The weak performance of the other PTFs could be related to the fact that the mountain soils of the basin are rich in 2:1 clay and high stoniness, which were not used as independent variables for PTFs to estimate the WR -33kPa. The authors are grateful to the Abdus Salam International Centre for Theoretical Physics (ICTP), Trieste, Italy, the Venezuelan Organic Law for Science and Technology (LOCTI), and the Council of Scientific and Humanistic Develop- ment (CDCH) of the Universidad Central de Venezuela, the Universidad de Lleida (Catalonia, Spain), and the Brazilian Re- search Council (CNPq) for the scholarships and funding.
-Multiple linear regression
-Soil stoniness
-Soil water content
(c) Springer International Publishing AG, part of Springer Nature 2018
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Article - Accepted version
Springer Verlag
         

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